Abstract
Reverse vaccinology is an outstanding strategy to identify antigens with high potential for vaccine development. Different parameters of five prediction programs were used to assess their sensitivity and specificity to identify B-cell epitopes of Chikungunya virus (CHIKV) strains reported in the IEDB database. The results, based on the use of 15 to 20 mer epitopes and the polyproteins to which they belong, were compared to establish the best parameters to optimize the prediction of antigenic peptides of the Mexican strain CHIKV AJV21562.1. LBtope showed the highest specificity when we used the reported epitopes and polyproteins but the worst sensitivity with polyproteins; ABCpred had similar specificity to LBtope only with the epitopes reported and showed moderate specificity when we used polyproteins for the predictions. Because LBtope was more reliable in predicting true epitopes, it was used as a reference program to predict and select six novel epitopes of the Mexican strain of CHIKV according to prediction frequency, viral genome localization, and non-homology with the human proteome. On the other hand, six bioinformatics programs were used with default parameters to predict T-cell epitopes in the CHIKV strains AJV21562.1 and AJV21561.1. The sequences of the polyproteins were analyzed to predict epitopes present in the more frequent HLA alleles of the Mexican population: DQA1*03011, DQA1*0401, DQA1*0501, DQB1*0201, DQB1*0301, DQB1*0302, and DQB1*0402. Fifteen predicted epitopes in the non-structural and 15 predicted epitopes in the structural polyprotein (9- to 16-mers) with the highest scores of each allele were compared to select epitopes with at least 80% identity. Next, the epitopes predicted with at least two programs were aligned to the human proteome, and 12 sequences without identity with the human proteome were identified as potential antigenic candidates. This strategy would be useful to evaluate vaccine candidates against other viral diseases affecting the countries of the Americas and to increase knowledge about these diseases.
Highlights
Chikungunya virus (CHIKV) is an enveloped, single-stranded, positive-sense RNA virus belonging to the genus Alphavirus of the family Togaviridae [1,2]
Twenty-four positive epitopes and 33 negative epitopes were selected from the IEDB database, in which they were registered with positive or highly positive immunoreactivity or negative against CHIKV antibodies in infected human sera (Table 1)
In order to improve the specificity and sensitivity of our prediction of B-cell epitopes, several thresholds in computational programs were used to analyze the prediction of control epitopes retrieved from the IEDB
Summary
Chikungunya virus (CHIKV) is an enveloped, single-stranded, positive-sense RNA virus belonging to the genus Alphavirus of the family Togaviridae [1,2]. Analyses of complete CHIKV genomes from viruses isolated in 2014 from 14 Caribbean islands, the Bahamas, and two mainland countries in the Americas confirmed that all belonged to the Asian genotype. They clustered together with the other Caribbean and mainland sequences isolated during the American outbreak, forming a monophyletic ‘Asian/American’ lineage that is divided into two well-supported clades [7]
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